Intelligence Complexity details a theory of intelligence complexity based on discrete levels of intelligence: Data, Information, Knowledge and Wisdom (DIKW). The report provides detailed descriptions of each of these defined levels of intelligence and puts forward a framework that can be used to measure the intelligence complexity of any intelligent system. Intelligence Complexity’s DIKW framework provides an alternative to the Turing Test as a measure of a system’s ability to reach defined levels of intelligence.

Intelligence Complexity also introduces a new concept (I = E x C) developed by author Michael Swetnam to explain what drives intelligent systems to learn. This theory posits that intelligence is inextricably linked to emotion, which is a key force that drives the development of human intelligence forward. The authors present a thermodynamic argument of emotion that attempts to explain the human intelligence system in terms of complexity, efficiency and entropy.

The authors of the Intelligence Complexity report and concepts include Michael Swetnam, Dr. Robert Hummel, Dr. Charles Mueller and Dr. Paul Syers. The work is the product of a two-year study of Potomac Institute’s Center For Revolutionary Scientific Thought (CReST) investigating the future societal impacts of artificial intelligence and the Big Data revolution. The formalization of DIKW as a measurement of intelligence has been granted a provisional US patent. This work is also the basis of a forthcoming book by Dr. Robert Hummel, “The Quest for Machine Intelligence: Climbing the Hierarchy of Intelligence Levels.”

The Center for Revolutionary Scientific Thought anticipates how science and technology will change our world and addresses complex problems with creative, revolutionary solutions. The Potomac Institute for Policy Studies is an independent, 501(c)(3), not-for-profit public policy research institute with a focus on science, technology, and national security issues.